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| Filter results10 paper(s) found. |
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1. Optimization of Forage Harvesting By Automatic Speed Control and Additive ApplicationEfficient use of machines is especially important in forage harvesting due to the short harvesting period and expensive machinery. To achieve the best efficiency, a harvesting machine, such as a loader wagon, should be used with optimal loading. Whereas overloading the machine can cause blockages in the cut-and-feed unit, underloading consumes more time and reduces the quality of the resulting silage. In addition, the quality can be improved by optimizing the dosage of the additive. Since the... A. Suokannas, J. Backman, A. Visala, A. Kunnas |
2. Path Generation Method with Steering Rate ConstraintThe practical way to generate a reference path in path tracking is to follow an adjacent swath. However, if the adjacent swath contains sharp turnings, the reference path will eventually contain sharper turn than the tractor is able to follow. This occurs especially in the corner of a field plot when the field is driven around. In the headland, the objective is to minimize the time to reach the next swath. The commonly known method to generate the shortest path between two arbitrary... J. Backman, T. Oksanen, A. Visala |
3. A Remote Interface for a Human-Robot Cooperative Vineyard Sprayer... Y. Edan, R. Berenstein, I. Ben-halevi |
4. Memory Based Learning: A New Data Mining Approach to Model and Interpret Soil Texture Diffuse Reflectance SpectraSuccessful estimation of spectrally active soil texture with Visible and Near-Infrared (VNIR, 400-1200 nm) and Short-Wave-Infrared (SWIR, 1200-2500 nm) spectroscopy depends mostly on the selection of an appropriate data mining algorithm. The aims of this paper were: to compare different data mining algorithms including Partial Least Squares Regression (PLSR), which is the most common technique in soil spectroscopy, Support Vector Machine Regression (SVMR), Boosted Regression Trees (BRT), and Memory... A. Gholizadeh, M. Saberioon, L. Borůvka |
5. Real-time Gauge Wheel Load Variability on Planter with Downforce Control During Field OperationDownforce control allows planters to maintain gauge wheel load across a range of soil resistance within a field. Downforce control is typically set for a target seed depth and either set to manually or automatically control the gauge wheel load. This technology uses load cells to actively regulate downforce on individual row units by monitoring target load on the gauge wheels. However, no studies have been conducted to evaluate the variability in gauge wheel load observed during planter operation... A. Sharda, S. Badua, D. Flippo, I. Ciampitti, T.W. Griffin |
6. Corn Nitrogen Fertilizer Recommendation Models Based on Soil Hydrologic Groups Aid in Predicting Economically Optimal Nitrogen RatesNitrogen (N) fertilizer recommendations that match corn (Zea mays L.) N needs maximize grower profits and minimize water quality consequences. However, spatial and temporal variability makes determining future N requirements difficult. Studies have shown no single soil or weather measurement is consistently increases accuracy, especially when applied over a regional scale, in predicting economically optimal N rate (EONR). Basing site N response on soil hydrological group could help account for... G.M. Bean, N.R. Kitchen, J.J. Camberato, R.B. Ferguson, F.G. Fernandez, D.W. Franzen, C.A. Laboski, E.D. Nafziger, J.E. Sawyer, P.C. Scharf |
7. Influence of Planter Downforce Setting and Ground Speed on Seeding Depth and Plant Spacing Uniformity of CornUniform seed placement improves seed-to-soil contact and requires proper selection of downforce control across varying field conditions. At faster ground speeds, downforce changes and it becomes critical to select the level of planter downforce settings to achieve the desired consistency of seed placement during planting. The objective of this study was to assess the effect of ground speed and downforce setting on seeding depth and plant spacing and to evaluate the relationship of ground speed... A. Sharda, S. Badua, I. Ciampitti, R. Strasser, T.W. Griffin |
8. Developing a Machine Learning and Proximal Sensing-based In-season Site-specific Nitrogen Management Strategy for Corn in the US MidwestEffective in-season site-specific nitrogen (N) management strategies are urgently needed to ensure both food security and sustainable agricultural development. Different active canopy sensor-based precision N management strategies have been developed and evaluated in different parts of the world. Recent studies evaluating several sensor-based N recommendation algorithms across the US Midwest indicated that these locally developed algorithms generally did not perform well when used broadly across... D. Li, Y. Miao, .G. Fernández, N.R. Kitchen, C. . Ransom, G.M. Bean, .E. Sawyer, J.J. Camberato, .R. Carter, R.B. Ferguson, D.W. Franzen, D.W. Franzen, D.W. Franzen, D.W. Franzen, C.A. Laboski, E.D. Nafziger, J.F. Shanahan |
9. The Impact of Row Unit Position on Planter Toolbar on Corn Crop Development: an Experimental StudyPrecision planting techniques are essential to grow corn successfully. Monitoring planter speed, row-unit bounce, and gauge-wheel load ensures high-quality seeding. Vertical vibration during planting can impede seed metering and delivery, causing planting variability. Row unit vibration increases with planting speed and can lead to spatial variability in planting. Therefore, the goals of this study were to 1) understand the influence of row unit location on its vertical vibration; and 2) compare... J. Peiretti, A. Sharda, S. Badua |
10. Avena: an Event-driven Software Framework for Informed Decisions and Actions in Cropping SystemsInteroperability is one of the enabling factors of real-time communications and data exchange between asynchronous data actors. Interoperability can be attained by introducing events to systems that extract data from consumed ground-truth event streams that utilize application-specific structures. Events are specific occurrences happening at a particular time and place. Event-data are observations of phenomena, or actions, as seen by different systems in Internet of Things (IoT) deployments, independent... F.A. Castiblanco rubio, M. Basir, A. Balmos, J. Krogmeier, D. Buckmaster |